Solutions from Montgomery, D. C. (2012) Design and Analysis of Experiments, Wiley, NY
Chapter 6
k
The 2 Factorial Design
Solutions
6.1. An engineer is interested in the effects of cutting speed (A), t
Solutions from Montgomery, D. C. (2012) Design and Analysis of Experiments, Wiley, NY
Chapter 3
Experiments with a Single Factor: The Analysis of Variance
Solutions
3.1. An experimenter has conducted
Solutions from Montgomery, D. C. (2012) Design and Analysis of Experiments, Wiley, NY
Chapter 8
Two-Level Fractional Factorial Designs
Solutions
8.1. Suppose that in the chemical process development e
Solutions from Montgomery, D. C. (2012) Design and Analysis of Experiments, Wiley, NY
Chapter 12
Robust Parameter Design and Process Robustness Studies
Solutions
12.1. Reconsider the leaf spring exper
Solutions from Montgomery, D. C. (2012) Design and Analysis of Experiments, Wiley, NY
Chapter 13
Experiments with Random Factors
Solutions
13.1. An experiment was performed to investigate the capabili
Solutions from Montgomery, D. C. (2012) Design and Analysis of Experiments, Wiley, NY
Chapter 9
Three-Level and Mixed-Level
Factorial and Fractional Factorial Design
Solutions
9.1. The effects of deve
Solutions from Montgomery, D. C. (2012) Design and Analysis of Experiments, Wiley, NY
Chapter 5
Introduction to Factorial Designs
Solutions
5.1. The following output was obtained from a computer progr
Solutions from Montgomery, D. C. (2012) Design and Analysis of Experiments, Wiley, NY
Chapter 10
Fitting Regression Models
Solutions
10.1. The tensile strength of a paper product is related to the amo
Solutions from Montgomery, D. C. (2012) Design and Analysis of Experiments, Wiley, NY
Chapter 7
Blocking and Confounding in the 2k Factorial Design
Solutions
7.1 Consider the experiment described in P
Solutions from Montgomery, D. C. (2008) Design and Analysis of Experiments, Wiley, NY
Chapter 4
Randomized Blocks, Latin Squares, and Related Designs
Solutions
4.1.
The ANOVA from a randomized complet
Solutions from Montgomery, D. C. (2012) Design and Analysis of Experiments, Wiley, NY
Chapter 2
Simple Comparative Experiments
Solutions
2.1. Computer output for a random sample of data is shown below
Solutions from Montgomery, D. C. (2012) Design and Analysis of Experiments, Wiley, NY
Chapter 11
Response Surface Methods and Designs
Solutions
11.1. A chemical plant produces oxygen by liquefying air
Formal inference
Important feature of statistical analysis is assessment of
uncertainty in the conclusions
Math 664 Principles of Statistical Analysis
Lecture Set 10: Inference and variable selection
Example G
Math 664 Methods for Statistical Consulting
Lecture 2: Case Study from Example G
Cost of construction of nuclear
power plants
Ji Meng Loh
New Jersey Institute of Technology
Cullimore 211C
Em
Preliminary analysis - what to consider
Although it is tempting to dive straight into formal statistical
analysis, it is often useful to start with a thoughtful and
systematic exploration of a new dat
Broad aims in the design of studies
Avoid systematic error, i.e. errors from irrelevant sources that
do not cancel out in the long run
Math 664 Methods for Statistical Consulting
Lecture 6
Design of S
Collecting data
Math 664 Methods for Statistical Consulting
Lecture 5
Design of Studies; observational studies
Experiments and sampling
Ji Meng Loh
New Jersey Institute of Technology
Cullimore 211C
Te
Example
Math 664 Principles of Statistical Analysis
Lecture 7
Example Q of Applied Statistics
Strength of cotton yarn
Ji Meng Loh
New Jersey Institute of Technology
Cullimore 211C
Tel: x2949
Lecture 7
Example V from Applied Statistics
Math 664 Methods Statistical Consulting
Lecture Set 9
Example V from Applied Statistics
A retrospective study with binary data
Ji Meng Loh
New Jersey Institute of Tec
Logistic regression for binary response
When the response is binary, i.e. Y can take values 0 or 1, the
mean of Y , , is equal to p P(Y = 1).
Math 664 Methods for Statistical Consulting
Lecture Set 8:
Newtons law
We will look at the simple example of investigating one of
Newtons laws.
Math 664 Methods for Statistical Consulting
Lecture 2: Investigating Newtons Laws
If an object is dropped from a re
Introduction
Statistical analysis - understand unexplained and haphazard
variation to explain some phenomenon
Math 664 Methods for Statistical Consulting
Lecture 1: Principles for Statistical Analysis
Math 361, Problem set 9
Due 11/8/10
1. (2.2.3) Let X1 and X2 have the joint pdf h(x1 , x2 ) = 2ex1 x2 , 0 < x1 <
x2 < , zero elsewhere. Find the joint pdf of Y1 = 2X1 and Y2 = X2 X1 .
Answer: We have
Math 361, Problem Set 2
November 4, 2010
Due: 11/1/10
1. (2.1.5) Given that the nonnegqative function g (x) has the property that
g (x)dx = 1, show that
0
f (x1 , x2 ) =
2g ( x2 + x2 )
1
2
x2 + x2
1
2
Principles of applied statistics
Principles of measurement
Math 664 Principles of Statistical Analysis
Preliminary analysis
Ji Meng Loh
New Jersey Institute of Technology
Cullimore 211C
Tel: x2949
Lec
Methods for Statistical Consulting
Classication
Math 664 Methods for Statistical Consulting
Lecture 8
Classication and Regression Trees
Ji Meng Loh
Random Forests, Boosted Trees
New Jersey Institute o
Principles of Statistical Analysis
Math 664 Principles of Statistical Analysis
Lecture 7
Techniques of formal inference
Ji Meng Loh
Variable selection techniques
New Jersey Institute of Technology
Cul
Today
Finish the R section from last lecture
Math 664 Principles of Statistical Analysis
Example C from Applied Statistics
Ji Meng Loh
Design of studies; observational studies
New Jersey Institute of
Methods for Statistical Consulting
Math 664 Methods for Statistical Consulting
Lecture 9
Classication and Regression Trees
Ji Meng Loh
Bagging, Random Forests, Boosted Trees
New Jersey Institute of Te
Introduction
Statistical analysis - understand unexplained and haphazard
variation to explain some phenomenon
Math 664 Methods for Statistical Consulting
Statistical consulting - it involves
Ji Meng L